2021/11/16 · View a PDF of the paper titled Phase function estimation from a diffuse optical image via deep learning, by Yuxuan Liang and 4 other authors.

Here we design a convolutional neural network (CNN) to estimate the phase function from a diffuse optical image without any explicit assumption on the form of ...

Here we design a convolutional neural network to estimate the phase function from a diffuse optical image without any explicit assumption on the form of the ...

Approach.Here we design a convolutional neural network (CNN) to estimate the phase function from a diffuse optical image without any explicit assumption on the ...

In recent years, machine learning methods were reported to estimate the parameters of the phase function of a particular form such as the Henyey–Greenstein ...

Approach. Here we design a convolutional neural network (CNN) to estimate the phase function from a diffuse optical image without any explicit assumption on the ...

In this paper, we propose an approach based on deep learning for direct estimation of phase derivatives in digital holographic interferometry. Using a Y-Net ...

2022/01/19 · This article discusses the current state-of-the-art diffuse optical tomography systems and comprehensively reviews the deep learning algorithms used in image ...

In this paper, we present an end-to-end compressible phase imaging method based on deep neural networks, which can implement phase estimation using only binary ...

2022/02/23 · In this review, we present an overview of the current status and the latest progress of deep-learning technologies in the field of optical metrology.